Abstract: The classic K-Nearest Neighbor (KNN) classification algorithm is widely used in text classification. This paper proposes an efficient algorithm for text classification by improving the ...

To understand and implement the K-Nearest Neighbors (KNN) algorithm for solving classification problems using the Iris dataset. This project demonstrates data preprocessing, model training, evaluation ...

ABSTRACT: Accurate prediction of malaria incidence is indispensable in helping policy makers and decision makers intervene before the onset of an outbreak and potentially save lives. Various ...

Introduction: Integrating immune repertoire sequencing data with single cell sequencing data offers profound insights into the diversity of immune cells and their dynamic changes across various ...

Introduction: The health status of bearings is an essential prerequisite to ensure the safe and stable operation of vehicles. However, the negative impact of covariate shifts among data channels on ...

This project detects spam messages in SMS, including those written in regional languages typed in English. It uses an extended SMS dataset and applies the Monte Carlo method with various supervised ...

Abstract: K-nearest neighbor classification algorithm can quickly deal with the classification problem in this paper, but when calculating the similarity, it will assign the same weight to all ...